jupyter-lab

Getting DLL error with 'jupyter lab' command in Anaconda Installation: Details for system: conda 4.5.11 Python 3.7.0 jupyter 4.4.0 Height of weirdness is that I am able to launch jupyter lab from Anaconda Navigator, but ' jupyter lab ' is not working and throwing below exception: Traceback (most recent call last): File "c:\ml\installed_tools\anaconda3\lib\runpy.py", line 193, in _run_module_as_main "__main__", mod_spec) File "c:\ml\installed_tools\anaconda3\lib\runpy.py", line 85, in _run_code exec(code, run_globals) File "C:\ML\installed_tools\anaconda3\Scripts\jupyter-lab.EXE\__main__.py",

I created a virtual environment and installed ipython[all] and jupyter with pip. When I run jupyter lab , open a notebook, and try importing a package I installed inside the virtual environment, I get “ModuleNotFoundError.” Running ipython in the console and importing works. Also, which jupyter does point me to the right executable in the virtual environment. In addition to installing jupyter , I need to install jupyter lab . Otherwise, even the virtual environment jupyter executable actually silently falls back to the system Jupyter Lab installation. 来源： https://stackoverflow.com/questions

I'm using plotly at jupyter lab, but I'm getting a blanked output. I'm having exactly the same problem described here: plotly.offline.iplot gives a large blank field as its output - why? And I tried what they suggested in the answers, but it didn't work. Here is the code I'm using: import pandas as pd import numpy as np %matplotlib inline from plotly.offline import download_plotlyjs, init_notebook_mode, plot, iplot init_notebook_mode(connected=True) cf.go_offline() df = pd.DataFrame(np.random.randn(100,4), columns='A B C D'.split()) df2 = pd.DataFrame({'category':['A','B','C'], 'values':[32,43

I want to create an interactive JupyterLab Notebook application, and I need to create a series of custom Widgets. So I started looking into this matter, and the more I look the more confused I become. To make things simple I will ask a bunch of simple questions: One of the most common ways to use widgets on Jupyter Notebooks is to use the ipywidgets library. Right? Unlike the classic Notebook, the Notebook of JupyterLab cannot render JavaScript directly. As a result, the tutorials about custom widget creation in the ipywidgets docs are impossible to run on JupyterLab. Right? If one wants to

In theory, the prediction should be constant as the weights have a fixed size. How do I get my speed back after compile (without the need to remove optimizer)? See associated experiment: https://nbviewer.jupyter.org/github/off99555/TensorFlowExperiments/blob/master/test-prediction-speed-after-compile.ipynb?flush_cache=true ULTIMATE CULPRIT : self._experimental_run_tf_function = True . It's experimental . But it's not actually bad. To any TensorFlow devs reading: clean up your code . It's a mess. And it violates important coding practices, such as one function does one thing ; _process_inputs

I've been using Jupyter Notebooks for a couple of years now. I've just headed over to Jupyter Lab, but I've found the lack of shortcuts to be a burden. For example, I noticed that I can search for commands in the left hand palette. But I can't seem to easily bind them to a keyboard shortcut. Is this even possible? For example, I want to collapse the current cell output with "O" and collapse all code cells with "Shift O". This question is answered on GitHub here . You can also look here for the correct command names to enter in your keyboard shortcut user overrides because they are not always